{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:49:58Z","timestamp":1792788598411,"version":"4.5.0"},"reference-count":18,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T00:00:00Z","timestamp":1658361600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Crisis"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:p>Producing statistically robust profiles of small or \u2018hard-to-reach\u2019 populations has always been a challenge for researchers. Since surveying the wider population in order to capture a large enough sample of cases is usually too costly or impractical, researchers have been opting for \u2018snowballing\u2019 or \u2018time-location sampling\u2019. The former does not allow for claims to representativeness, and the latter struggles with under-coverage and estimating confidence intervals. Respondent Driven Sampling (RDS) is a method that combines snowballing sampling with an analytical algorithm that corrects for biases that arise in snowballing. For all its advantages, a major weakness of RDS has been around data collection. Traditionally done on-site, the process is costly and lengthy. When done online, it is cheaper and faster but under a serious threat from fraud, compromising data quality and validity of findings. This paper describes a real-life application of a RDS data collection system that maximizes fraud prevention while still benefiting from low cost and speedy data collection.<\/jats:p>","DOI":"10.1371\/journal.pone.0270673","type":"journal-article","created":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T13:49:05Z","timestamp":1658411345000},"page":"e0270673","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":17,"title":["Smartphone-based Respondent Driven Sampling (RDS): A methodological advance in surveying small or \u2018hard-to-reach\u2019 populations"],"prefix":"10.1371","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0557-173X","authenticated-orcid":true,"given":"Filip Lukasz","family":"Sosenko","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Glen","family":"Bramley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2022,7,21]]},"reference":[{"key":"pone.0270673.ref001","doi-asserted-by":"crossref","DOI":"10.1201\/9780429296284","volume-title":"Sampling: design and analysis","author":"SL Lohr","year":"2019","edition":"2"},{"key":"pone.0270673.ref002","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1007\/s11524-012-9676-8","article-title":"Statistical methods for the analysis of time-location sampling data","volume":"89","author":"JM Karon","year":"2012","journal-title":"J Urban Health Bull N Y Acad Med"},{"key":"pone.0270673.ref003","doi-asserted-by":"crossref","first-page":"174","DOI":"10.2307\/3096941","article-title":"Respondent-Driven Sampling: A New Approach to the Study of Hidden Populations","volume":"44","author":"DD Heckathorn","year":"1997","journal-title":"Soc Probl"},{"key":"pone.0270673.ref004","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1093\/biostatistics\/kxu061","article-title":"Design-based inference in time-location sampling","volume":"16","author":"L Leon","year":"2015","journal-title":"Biostatistics"},{"key":"pone.0270673.ref005","volume-title":"The scale, causes and impacts of homelessness among EEA citizens","author":"G Bramley","year":"2021"},{"key":"pone.0270673.ref006","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1111\/j.0081-1750.2004.00152.x","article-title":"Sampling and Estimation in Hidden Populations Using Respondent-Driven Sampling","volume":"34","author":"MJ Salganik","year":"2004","journal-title":"Sociol Methodol"},{"key":"pone.0270673.ref007","first-page":"smx018","article-title":"Evaluating Variance Estimators for Respondent-Driven Sampling","volume":"2017","author":"MW Spiller","year":"2017","journal-title":"J Surv Stat Methodol"},{"key":"pone.0270673.ref008","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1186\/s13104-016-1965-y","article-title":"Lessons learned from respondent-driven sampling recruitment in Nairobi: experiences from the field","volume":"9","author":"J Okal","year":"2016","journal-title":"BMC Res Notes"},{"key":"pone.0270673.ref009","doi-asserted-by":"crossref","unstructured":"Tyldum G, Johnston L (eds). Applying Respondent Driven Sampling to Migrant Populations: Lessons from the Field. Palgrave Macmillan UK. 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